Next we might consider the loss of missclassification: In a computer
vision task, pixel missclassifications are to be expected and can
be smoothed over. Computational complexity however can severely
limit the possible applications of an algorithm. As [1]}
note, using a bigger dataset can be more advantageous than using
the best algorithm, so we would favour an efficient procedure over a
very accurate one, because it would allow us to train on a bigger training
set. Since the variables are likely to be correlated,
ranking will give bad results.
